In many machine vision applications, such as probe mark inspection (PMI), it is necessary to adjust the parameters of a machine vision tool to ensure satisfactory performance and results. However, manually adjusting the parameters, such as registration and inspection parameters, often requires the expertise of an experienced vision engineer, and even in that case, finding a good set of parameters can be a very time-consuming process.
Finding a good set of parameters is time-consuming, and often challenging, because the set of parameters define a large multi-dimensional space that may need to be searched thoroughly to find an acceptable parameter set. Manual approaches to finding a good parameter set are especially difficult and time-consuming when the parameter space includes continuous variables, or many discrete values per dimension.